Abstract

Human interaction with social networking services (SNS) is currently a very active research area. In recent years, microblogs and social networking sites have become increasingly popular among online communities. Examples of such sites are Facebook, Twitter, Google+, My Space, Hi5, and WAYN. Micro log posts, such as tweets, allow users to broadcast their ideas in short form of text, voice, or images, using mobile devices and computers. Modern mobile devices- such as feature phones, smart phones, tablets, and net books- are internet-capable and feature various convenient hardware capabilities for building and managing social relationships between people. Text and speech enriched with emotions is one of the major ways of exchanging ideas, especially via telephony and SNS. By analyzing a voice stream using a Hidden Markov Model (HMM) and Log Frequency Cepstral Coefficients (LFPC) based system, different emotions can be recognized. Using a simple Java client, recognized emotions can be delivered to a sever as an index. A mobile client can then retrieve the emotion and display it through colored icons. Each emotion is mapped to a particular color, as it is natural to use colors to represent various expressions. We believe that with the help of this application one could conceivably change one's way of talking or avoid chatting with somebody whose emotional state is negative! By analysing a text snippet using C4.5 decision tree, Support Vector Machine (SVM), different emotions can be recognized. Not only for voice, these methods can be used when a user doing text message. NTT Do Como provides a service called iappli as an integrated platform for Java-based application programs. Because of its compatibility with Java, maturity, and wide usage, we chose this platform to display emotions of human voice through colored icons. In the mobile interface there are displayed icons representing different users and different emotions are represented using colors. Each emotion is mapped to a particular color. This paper proposes an emotion expression systems. Human emotion can be expressed through many kinds of media such as speech, image, facial expression, animating and so forth. This paper focuses on emotion expression using color and as avatar animations. We discuss here emotion extraction from speech.

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